System and mathematical modeling of quadrotor dynamics

Goodman, Jacob; Kim, Jin-Ho; Gadsden, S. Andrew; Wilkerson, Stephen A.

doi:10.1117/12.2185196

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…The matrix ∈ (3) which is defined in the following form: Detailed information on mathematical modeling can be found in many papers such as [25,26].…”

Section: Problem Formulationmentioning

confidence: 99%

A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot

Razmavar

Talebi

Abdollahi

2021

IJEECS

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<span>In this article a novel composite control technique is introduced. We added a nonlinear disturbance observer to a nonlinear H_∞ control to form this composite controller. The quadrotor kinematics and dynamics is formulated using euler angles and parameters. After that, this nonlinear robust controller is developed for this flying robot attitude control for the outdoor conditions. Because under these conditions the flying robot, experiences both external disturbance and parametric uncertainty. Stability analysis is also presented to show the global asymptotical stability using a Lyapunov function. The simulation results showed that the suggested composite controller had a better performance in comparison with a nonlinear H_∞ control scheme.</span>

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“…The matrix ∈ (3) which is defined in the following form: Detailed information on mathematical modeling can be found in many papers such as [25,26].…”

Section: Problem Formulationmentioning

confidence: 99%

A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot

Razmavar

Talebi

Abdollahi

2021

IJEECS

View full text Add to dashboard Cite

show abstract

“…The quadrotor is an under-actuated system with four inputs and six outputs, and the states are highly coupled. To control this system, modeling approaches are presented in [28]- [30]. The quadrotor can be controlled by varying thrust forces and moments generated by each rotor.…”

Section: Quadrotor Dynamicsmentioning

confidence: 99%

A Comprehensive Survey of Control Strategies for Autonomous Quadrotors

Kim,

Gadsden,

Wilkerson

2020

Preprint

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Over the past several decades there has been a constant increase in the use of Unmanned Aerial Systems (UAS). Hence, there has also been a growth in the number of control algorithms to service the many applications embodied by these vehicles. Initially UAS were made popular by the military for Reconnaissance, Intelligence, Surveillance, and Target Acquisition (RISTA) applications. Now-a-days UAS are used for everything from crop surveys to tourism. Nowhere is this more evident than with multi-rotor Unmanned Aerial Vehicle (UAV). This paper presents a survey of control methods for multi-rotor systems, namely quadrotors. In doing so, we hope to visualize a clear path to what additional capabilities might be needed in the future. In our examination, we review many of the notable research organizations and their efforts to expand the utility of multirotor aircraft. We also summarize the basic literature definitions and control strategies for autonomous quadrotors.

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“…Although the correct date of the first successful UAV flight is not clear, some circles claim that the history of UAVs dates back to 1849, when the Austrians launched 200 pilot-less balloons against the city of Venice [1]. Gradually, the use of drones diversified in many areas of aviation, and currently, UAVs are gaining a considerable acceptance because of their applications in a multitude of fields [2,3,4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Application specific drone simulators: Recent advances and challenges

Mairaj

Baba

Javaid

2019

Simulation Modelling Practice and Theory

116

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Over the past two decades, Unmanned Aerial Vehicles (UAVs), more commonly known as drones, have gained a lot of attention, and are rapidly becoming ubiquitous because of their diverse applications such as surveillance, disaster management, pollution monitoring, film-making, and military reconnaissance. However, incidents such as fatal system failures, malicious attacks, and disastrous misuses have raised concerns in the recent past. Security and viability concerns in drone-based applications are growing at an alarming rate. Besides, UAV networks (UAVNets) are distinctive from other ad-hoc networks. Therefore, it is necessary to address these issues to ensure proper functioning of these UAVs while keeping their uniqueness in mind. Furthermore, adequate security and functionality require the consideration of many parameters that may include an accurate cognizance of the working mechanism of vehicles, geographical and weather conditions, and UAVNet communication. This is achievable by creating a simulator that includes these aspects. A performance evaluation through relevant drone simulator becomes indispensable procedure to test features, configurations, and designs to demonstrate superiority to comparative schemes and suitability. Thus, it becomes of paramount importance to establish the credibility of simulation results by investigating the merits and limitations of each simulator prior to selection. Based on this motivation, we present a comprehensive survey of current drone simulators. In addition, open research issues and research challenges are discussed and presented.

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System and mathematical modeling of quadrotor dynamics

Cited by 9 publications

References 17 publications

A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot

A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot

A Comprehensive Survey of Control Strategies for Autonomous Quadrotors

Application specific drone simulators: Recent advances and challenges

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